The role of uncertainty and sentiment for intraday volatility connectedness between oil and financial markets

• Autorzy: Karol Szafranek , Michał Rubaszek , Gazi Salah Uddin
• Języki publikacji: EN

Abstrakty

EN

We quantify intraday volatility connectedness between oil and key financial assets and assess how it is related to uncertainty and sentiment measures. For that purpose, we integrate the well-known spillover methodology with a TVP VAR model estimated on a unique, vast dataset of roughly 300 thousand 5 minute quotations for crude oil, the US dollar, S&P 500 index, gold and US treasury prices. This distinguishes our investi- gation from previous studies, which usually employ relatively short samples of daily or weekly data and focus on connectedness between two asset classes. We contribute to the literature across three margins. First, we document that market connectedness at intraday frequency presents new picture on markets co-movement compared to the esti- mates obtained using daily data. Second, we show that at 5 minute frequency volatility is mostly transmitted from the stock market and absorbed by the bond and dollar markets, with oil and gold markets being occasionally important for volatility transmission. Third, we present evidence that daily averages of intraday connectedness measures respond to changes in sentiment and market-specific uncertainty. Interestingly, our results contrast with earlier findings, as they show that connectedness among markets decreases in periods of high volatility owing to market-specific factors. Our study points to the importance of using high-frequency data in order to better understand market dynamics(original abstract)

Słowa kluczowe

EN

Oil; Financial markets; Equity market

PL

Ropa naftowa; Rynki finansowe; Rynek akcji

• Czasopismo: Collegium of Economic Analysis SGH - Working Papers
• Rocznik: 2023
• Numer: nr 95
• Strony: 45

Twórcy

autor

Karol Szafranek

• SGH Warsaw School of Economics

autor

Michał Rubaszek

• SGH Warsaw School of Economics

autor

Gazi Salah Uddin

• Linköping University, Sweden

Bibliografia

• Adekoya, O. B., Oliyide, J. A., 2021. How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques. Resources Policy 70, 101898.
• Adekoya, O. B., Oliyide, J. A., Yaya, O. S., Al-Faryan, M. A. S., 2022. Does oil connect differently with prominent assets during war? Analysis of intraday data during the Russia-Ukraine saga." Resources Policy" 77, 102728.
• Akyildirim, E., Cepni, O., Moln´ar, P., Uddin, G. S., 2022. Connectedness of energy markets around the world during the COVID-19 pandemic." Energy Economics "109, 105900.
• Albulescu, C. T., Demirer, R., Raheem, I. D., Tiwari, A. K., 2019. Does the U.S. economic policy uncertainty connect financial markets? Evidence from oil and commodity currencies". Energy Economics" 83, 375-388.
• Algaba, A., Ardia, D., Bluteau, K., Borms, S., Boudt, K., 2020. Econometrics meets sentiment: An overview of methodology and applications. "Journal of Economic Surveys" 34 (3), 512-547.
• Anand, B., Paul, S., 2021. Oil shocks and stock market: Revisiting the dynamics." Energy Economics" 96, 105111.
• Antonakakis, N., Chatziantoniou, I., Gabauer, D., 2020. Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. "Journal of Risk and Financial Management" 13 (4).
• Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., Perez de Gracia, F., 2018. Oil volatility, oil and gas firms and portfolio diversification." Energy Economics" 70, 499- 515.
• Antonakakis, N., Gupta, R., Kollias, C., Papadamou, S., 2017. Geopolitical risks and the oil-stock nexus over 1899-2016." Finance Research Letters" 23, 165-173.
• Awartani, B., Aktham, M., Cherif, G., 2016. The connectedness between crude oil and financial markets: Evidence from implied volatility indices. "Journal of Commodity Markets" (1), 56-69.
• Awartani, B., Maghyereh, A. I., 2013. Dynamic spillovers between oil and stock markets in the Gulf Cooperation Council Countries. "Energy Economics "36, 28-42.
• Baker, S., Bloom, N., Davisc, S., Renaultd, T., 2021. Twitter-derived measures of economic uncertainty. Unpublished.20 URL https://www.policyuncertainty.com/media/Twitter_Uncertainty_5_13_2021.pdf
• Baker, S. R., Bloom, N., Davis, S. J., 2016. Measuring Economic Policy Uncertainty. "Quarterly Journal of Economics "131 (4), 1593-1636.
• Balcilar, M., Gupta, R., Wang, S., Wohar, M. E., 2020. Oil price uncertainty and movements in the US government bond risk premia." North American Journal of Economics and Finance" 52, 101147.
• Barunik, J., Krehl´ık, T., 2018. Measuring the frequency dynamics of financial connectedness and systemic risk. "Journal of Financial Econometrics "16 (2), 271-296.
• Beckmann, J., Czudaj, R., 2013. Oil prices and effective dollar exchange rates. "International Review of Economics & Finance" 27, 621-636.
• Benlagha, N., Karim, S., Naeem, M. A., Lucey, B. M., Vigne, S. A., 2022. Risk connectedness between energy and stock markets: Evidence from oil importing and exporting countries. Energy Economics 115, 106348.
• Bernanke, B. S., 1983. Irreversibility, uncertainty, and cyclical investment. "Quarterly Journal of Economics" 98 (1), 85-106.
• Bilgin, M. H., Gozgor, G., Lau, C. K. M., Sheng, X., 2018. The effects of uncertainty measures on the price of gold. "International Review of Financial Analysis" 58, 1-7.
• Birru, J., Young, T., 2022. Sentiment and uncertainty. "Journal of Financial Economics" 146 (3), 1148-1169.
• Bouri, E., Lei, X., Jalkh, N., Xu, Y., Zhang, H., 2021. Spillovers in higher moments and umps across US stock and strategic commodity markets. "Resources Policy" 72, 102060.
• Buckman, S. R., Shapiro, A. H., Sudhof, M., Wilson, D. J., 2020. News Sentiment in the Time of COVID-19. "FRBSF Economic Letter" 2020-08, 1-5.
• Caldara, D., Iacoviello, M., 2022. Measuring geopolitical risk. "American Economic Review" 112 (4), 1194-1225.
• Castelnuovo, E., 2023. Uncertainty before and during COVID-19: A survey." Journal of Economic Surveys", In Press.
• Chen, Y.-C., Rogoff, K. S., Rossi, B., 2010. Can exchange rates forecast commodity prices? "Quarterly Journal of Economics" 125 (3), 1145-1194.
• Cogley, T., Sargent, T. J., 2005. Drifts and volatilities: monetary policies and outcomes in the post WWII US." Review of Economic Dynamics "8 (2), 262-302.
• Corbet, S., Goodell, J. W., G¨unay, S., 2020. Co-movements and spillovers of oil and renewable firms under extreme conditions: New evidence from negative WTI prices during COVID-19." Energy Economics "92, 104978.
• Cui, J., Maghyereh, A., 2023. Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict." International Review of Financial Analysis" 86, 102520.
• Dąbrowski, M. A., Papież, M., Rubaszek, M., Śmiech, S., 2022. The role of economic development for the effect of oil market shocks on oil-exporting countries. Evidence from the interacted panel VAR model. "Energy Economics" 110, 106017.
• Dai, Z., Kang, J., 2021. Bond yield and crude oil prices predictability. "Energy Economics" 97, 105205.
• Dai, Z., Zhu, H., 2023. Dynamic risk spillover among crude oil, economic policy uncertainty and Chinese financial sectors. "International Review of Economics & Finance" 83, 421-450.
• Dai, Z., Zhu, H., Zhang, X., 2022. Dynamic spillover effects and portfolio strategies between crude oil, gold and Chinese stock markets related to new energy vehicle. "Energy Economics "109, 105959.
• Demirer, R., Ferrer, R., Shahzad, S. J. H., 2020. Oil price shocks, global financial markets and their connectedness. "Energy Economics "88, 104771.
• Diebold, F. X., Yilmaz, K., 2012. Better to give than to receive: Predictive directional measurement of volatility spillovers." International Journal of Forecasting" 28 (1), 57-66.
• Diebold, F. X., Yilmaz, K., 2014. On the network topology of variance decompositions: Measuring the connectedness of financial firms. "Journal of Econometrics "182 (1), 119- 134.
• Eicher, T. S., Papageorgiou, C., Raftery, A. E., 2011. Default priors and predictive performance in Bayesian model averaging, with application to growth determinants. "Journal of Applied Econometrics" 26 (1), 30-55.
• Farid, S., Kayani, G. M., Naeem, M. A., Shahzad, S. J. H., 2021. Intraday volatility transmission among precious metals, energy and stocks during the COVID-19 pandemic. "Resources Policy" 72, 102101.
• Fern´andez, C., Ley, E., Steel, M. F., 2001. Benchmark priors for Bayesian model averaging. "Journal of Econometrics" 100 (2), 381-427.
• Gao, R., Zhao, Y., Zhang, B., 2021. The spillover effects of economic policy uncertainty on the oil, gold, and stock markets: Evidence from China. "International Journal of Finance & Economics "26 (2), 2134-2141.
• Gong, X., Xu, J., 2022a. Geopolitical risk and dynamic connectedness between commodity markets. "Energy Economics" 110, 106028.
• Gong, X., Xu, J., 2022b. Geopolitical risk and dynamic connectedness between commodity markets. "Energy Economics" 110, 106028.
• Gormus, A., Nazlioglu, S., Soytas, U., 2018. High-yield bond and energy markets." Energy Economics "69, 101-110.
• Hoeting, J. A., Madigan, D., Raftery, A. E., Volinsky, C. T., 1999. Bayesian Model Averaging: A Tutorial. "Statistical Science" 14 (4), 382-401.
• Husain, S., Tiwari, A. K., Sohag, K., Shahbaz, M., 2019. Connectedness among crude oil prices, stock index and metal prices: An application of network approach in the USA. "Resources Policy" 62, 57-65.
• Iqbal, N., Bouri, E., Grebinevych, O., Roubaud, D., 2023. Modelling extreme risk spillovers in the commodity markets around crisis periods including COVID19. "Annals of Operations Research", In Press.
• Kang, W., Ratti, R. A., Yoon, K. H., 2014. The impact of oil price shocks on U.S. bond market returns. "Energy Economics" 44, 248-258.
• Kass, R. E., Raftery, A. E., 1995. Bayes Factors. "Journal of the American Statistical Association" 90 (430), 773-795.
• Koop, G., Korobilis, D., 2013. Large time-varying parameter VARs." Journal of Econometrics" 177 (2), 185-198.
• Koop, G., Korobilis, D., 2014. A new index of financial conditions. "European Economic Review" 71, 101-116.
• Koop, G., Pesaran, M., Potter, S. M., 1996. Impulse response analysis in nonlinear multivariate models. "Journal of Econometrics "74 (1), 119 - 147.
• Ley, E., Steel, M. F., 2009. On the effect of prior assumptions in Bayesian model averaging with applications to growth regression. "Journal of Applied Econometrics "24 (4), 651- 674.
• Li, S., Tu, D., Zeng, Y., Gong, C., Yuan, D., 2022. Does geopolitical risk matter in crude oil and stock markets? Evidence from disaggregated data. "Energy Economics" 113, 106191.
• Lubik, T. A., Matthes, C., Owens, A., 2016. Beveridge curve shifts and time-varying parameter VARs." Economic Quarterly" (3Q), 197-226.
• Luo, J., Ji, Q., 2018. High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets. "Energy Economics "76, 424-438.
• Ma, Y.-R., Zhang, D., Ji, Q., Pan, J., 2019. Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter? "Energy Economics" 81, 536-544.
• Maghyereh, A., Abdoh, H., 2022. COVID-19 and the volatility interlinkage between bitcoin and financial assets. "Empirical Economics "63 (6), 2875-2901.
• Maghyereh, A. I., Awartani, B., Bouri, E., 2016. The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes. "Energy Economics" 57, 78-93.
• Malik, F., Umar, Z., 2019. Dynamic connectedness of oil price shocks and exchange rates. "Energy Economics" 84, 104501.
• Mensi, W., Ali, S. R. M., Vo, X. V., Kang, S. H., 2022a. Multiscale dependence, spillovers, and connectedness between precious metals and currency markets: A hedge and safehaven analysis. "Resources Policy" 77, 102752.
• Mensi, W., Vo, X. V., Kang, S. H., 2022b. COVID-19 pandemic's impact on intraday volatility spillover between oil, gold, and stock markets. "Economic Analysis and Policy" 74, 702-715.
• Moral-Benito, E., 2016. Growth empirics in panel data under model uncertainty and weak exogeneity. "Journal of Applied Econometrics" 31 (3), 584-602.
• Naeem, M. A., Karim, S., Yarovaya, L., Lucey, B. M., 2023. COVID-induced sentiment and the intraday volatility spillovers between energy and other ETFs. "Energy Economics" 122, 106677.
• Narayan, P. K., Narayan, S., Zheng, X., 2010. Gold and oil futures markets: Are markets efficient? "Applied Energy "87 (10), 3299-3303.
• Nazlioglu, S., Gupta, R., Bouri, E., 2020. Movements in international bond markets: The role of oil prices. "International Review of Economics & Finance" 68, 47-58.
• Obstfeld, M., Zhou, H., 2023. The global dollar cycle. NBER Working Papers 31004, National Bureau of Economic Research.
• Okhrin, Y., Uddin, G. S., Yahya, M., 2023. Nonlinear and asymmetric interconnectedness of crude oil with financial and commodity markets. "Energy Economics" 125, 106853.
• Ozcelebi, O., Tokmakcioglu, K., 2022. Assessment of the asymmetric impacts of the geopolitical risk on oil market dynamics. "International Journal of Finance & Economics "27 (1), 275-289.
• Pastor, L., Verones, P., 2012. Uncertainty about government policy and stock prices. "Journal of Finance" 67 (4), 1219-1264.
• Peng, C., Zhu, H., Guo, Y., Chen, X., 2018. Risk spillover of international crude oil to China's firms: Evidence from granger causality across quantile. "Energy Economics "72, 188-199.
• Pesaran, H., Shin, Y., 1998. Generalized impulse response analysis in linear multivariate models. "Economics Letters" 58 (1), 17 - 29.
• Phan, D. H. B., Sharma, S. S., Narayan, P. K., 2016. Intraday volatility interaction between the crude oil and equity markets." Journal of International Financial Markets, Institutions and Money" 40, 1-13.
• Primiceri, G. E., 2005. Time varying structural vector autoregressions and monetary policy. "Review of Economic Studies" 72 (3), 821-852.
• Raftery, A. E., Madigan, D., Hoeting, J. A., 1997. Bayesian model averaging for linear regression models. "Journal of the American Statistical Association" 92 (437), 179-191.
• Rehman, M. U., Shahzad, S. J. H., Uddin, G. S., Hedstr¨om, A., 2018. Precious metal returns and oil shocks: A time varying connectedness approach. "Resources Policy" 58, 77-89.
• Sala-i-Martin, X., Doppelhofer, G., Miller, R. I., 2004. Determinants of long-term growth: A Bayesian Averaging of Classical Estimates (BACE) approach. "American Economic Review "94 (4), 813-835.
• Sharif, A., Aloui, C., Yarovaya, L., 2020. Covid-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the us economy: Fresh evidence from the wavelet-based approach. "International Review of Financial Analysis "70, 101496.
• Smiech, S., Papiez, M., Rubaszek, M., Snarska, M., 2021. The role of oil price uncertainty shocks on oil-exporting countries. "Energy Economics" 93, 105028.
• Szafranek, K., Kwas, M., Szafra´nski, G., Wo´sko, Z., 2020. Common determinants of credit default swap premia in the North American oil and gas industry. A panel BMA approach." Energies" 13 (23), 6327.
• Szafranek, K., Papiez, M., Rubaszek, M., Smiech, S., 2023a. How immune is the connectedness of European natural gas markets to exceptional shocks? "Resources Policy "85, 103917.
• Szafranek, K., Rubaszek, M., 2023. Have European natural gas prices decoupled from crude oil prices? Evidence from TVP-VAR analysis. "Studies in Nonlinear Dynamics & Econometrics", In Press.
• Szafranek, K., Rubaszek, M., Uddin, G. S., 2023b. Which uncertainty measure is most informative? a time-varying connectedness perspective. Unpublished. URL https://ssrn.com/abstract=4360009
• Uddin, G. S., Bekiros, S., Ahmed, A., 2018. The nexus between geopolitical uncertainty and crude oil markets: An entropy-based wavelet analysis. "Physica A: Statistical Mechanics and its Applications" 495, 30-39.
• Umar, Z., Abrar, A., Hadhri, S., Sokolova, T., 2023. The connectedness of oil shocks, green bonds, sukuks and conventional bonds." Energy Economics" 119, 106562.
• Umar, Z., Aharon, D. Y., Esparcia, C., AlWahedi, W., 2022. Spillovers between sovereign yield curve components and oil price shocks. "Energy Economics "109, 105963.
• Wang, L., Ruan, H., Hong, Y., Luo, K., 2023a. Detecting the hidden asymmetric relationship between crude oil and the US dollar: A novel neural Granger causality method. "Research in International Business and Finance" 64, 101899.
• Wang, Z.-X., Liu, B.-Y., Fan, Y., 2023b. Network connectedness between China's crude oil futures and sector stock indices. "Energy Economics", 106848.
• Wiggins, S., Etienne, X. L., 2017. Turbulent times: Uncovering the origins of US natural gas price fluctuations since deregulation. "Energy Economics" 64, 196-205.
• Wu, H., Zhu, H., Huang, F., Mao, W., 2023. How does economic policy uncertainty drive time-frequency connectedness across commodity and financial markets? "North American Journal of Economics and Finance "64, 101865.
• Zhang, D., 2017. Oil shocks and stock markets revisited: Measuring connectedness from a global perspective. "Energy Economics" 62, 323-333.
• Zhang, H., Demirer, R., Huang, J., Huang, W., Tahir Suleman, M., 2021. Economic policy uncertainty and gold return dynamics: Evidence from high-frequency data. "Resources Policy" 72.
• Zhang, Y.-J., Wei, Y.-M., 2010. The crude oil market and the gold market: Evidence for cointegration, causality and price discovery. "Resources Policy" 35 (3), 168-177.